Machine learning model to predict vehicle electrification impacts on urban air quality and related human health effects

Air pollution is a prevailing environmental problem in cities worldwide. The future vehicle electrification (VE), which in Europe will be importantly fostered by the ban of thermal engines from 2035, is expected to have an important effect on urban air quality. Machine learning models represent an optimal tool for predicting changes in air pollutants concentrations in the context of future VE. For the city of Valencia (Spain), a XGBoost (eXtreme Gradient Boosting package) model was used in combination with SHAP (SHapley Additive exPlanations) analysis, both to investigate the importance of different factors explaining air pollution concentrations and predicting the effect of different levels of VE. The model was trained with 5 years of data including the COVID-19 lockdown period in 2020, in which mobility was strongly reduced resulting in unprecedent changes in air pollution concentrations. The interannual meteorological variability of 10 years was also considered in the analyses. For a 70% VE, the model predicted: 1) improvements in nitrogen dioxide pollution (-34% to -55% change in annual mean concentrations, for the different air quality stations), 2) a very limited effect on particulate matter concentrations (-1 to -4% change in annual means of PM_2.5 and PM₁₀), 3) heterogeneous responses in ground-level ozone concentrations (-2% to +12% change in the annual means of the daily maximum 8-h average concentrations). Even at a high VE increase of 70%, the 2021 World Health Organization Air Quality Guidelines will be exceeded for all pollutants in some stations. VE has a potentially important impact in terms of reducing NO₂-associated premature mortality, but complementary strategies for reducing traffic and controlling all different air pollution sources should also be implemented to protect human health.

Environmental and economic benefits of electric, hybrid and conventional vehicle treatment: A case study of Lithuania

Reuse, recovery, and recycling of end-of-life vehicles (ELVs) are encouraged owing to various economic and environmental benefits. Automotive remanufacturing serves as a specific circular marketing system for the reuse of recovered parts that can bring economic benefits for both dismantling companies and consumers. This study aimed to reveal the economic and environmental benefits of the end-of-life treatment of electric, hybrid, and conventional passenger cars. This research presents an economic assessment of the reuse of ELV parts based on a material flow analysis (MFA) and a practical analysis of the prices of these parts in the Lithuanian market. The environmental assessment of the reuse of ELV parts was performed using an MFA, the CO₂ equivalents for the production of different materials, and a life cycle assessment methodology. The results showed that 38% of all electric and hybrid ELV parts, and 27% and 28% of diesel- and petrol-powered ELV parts, respectively, can be sold (reused). The economic benefit across all four types of ELVs could amount to savings of up to 12,739 Eur and 51,281 Eur for the dismantlers and passenger car consumers, respectively. The greatest CO₂ savings result from reusing the parts of electric ELVs, whilst the lowest savings come from petrol ELVs.

Using agricultural residues for sustainable transportation biofuels in 2050: Case of West Africa

This article focuses on the use of biomass to produce transportation fuels such as synthetic natural gas, bioethanol and electricity under a sustainable scenario in West Africa in 2050. The aim of this work was to evaluate the feasibility of producing such biofuels using agricultural residues as feedstock in the studied area. The potential of biomass from ten agricultural residues was estimated in R environment using FAO data. Options were analyzed in order to generate portfolios of transportation fuels based on energy indicators, biomass availability and scenarios of technological progress. The optimal allocation varied from one country to the other, showing a fair tradeoff between the objective functions.